std::cauchy_distribution

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std::cauchy_distribution
Member functions
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Generation
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Defined in header <random>
template< class RealType = double >
class cauchy_distribution;
 (since C++11)

Produces random numbers according to a Cauchy distribution (also called Lorentz distribution):

f(x; a,b) = ⎛
⎜
⎝bπ ⎡
⎢
⎣1 + ⎛
⎜
⎝
x - a
b
⎞
⎟
⎠2
⎤
⎥
⎦⎞
⎟
⎠-1

std::cauchy_distribution satisfies all requirements of RandomNumberDistribution.

Template parameters

RealType - The result type generated by the generator. The effect is undefined if this is not one of float, double, or long double.

Member types

Member type Definition
result_type(C++11) RealType
param_type(C++11) the type of the parameter set, see RandomNumberDistribution.

Member functions

(C++11)
 constructs new distribution
(public member function)
(C++11)
 resets the internal state of the distribution
(public member function)
Generation
(C++11)
 generates the next random number in the distribution
(public member function)
Characteristics
returns the distribution parameters
(public member function)
(C++11)
 gets or sets the distribution parameter object
(public member function)
(C++11)
 returns the minimum potentially generated value
(public member function)
(C++11)
 returns the maximum potentially generated value
(public member function)

Non-member functions

(C++11)(C++11)(removed in C++20)
 compares two distribution objects
(function)
(C++11)
 performs stream input and output on pseudo-random number distribution
(function template)

Example

Run this code
#include <algorithm>
#include <cmath>
#include <iomanip>
#include <iostream>
#include <map>
#include <random>
#include <vector>
 
template <int Height = 5, int BarWidth = 1, int Padding = 1, int Offset = 0,
          bool DrawMinMax = true, class Sample>
void draw_vbars(Sample const& s) {
    static_assert((Height > 0) && (BarWidth > 0) && (Padding >= 0) && (Offset >= 0));
    auto cout_n = [](auto const& v, int n) { while (n-- > 0) std::cout << v; };
    const auto [min, max] = std::minmax_element(std::cbegin(s), std::cend(s));
    std::vector<std::div_t> qr;
    for (float e : s) {
        qr.push_back(std::div(std::lerp(0.f, Height*8, (e - *min)/(*max - *min)), 8));
    }
    for (auto h{Height}; h-- > 0 ;) {
        cout_n(' ', Offset);
        for (auto [q, r] : qr) {
            char d[] = "█"; // == { 0xe2, 0x96, 0x88, 0 }
            q < h ? d[0] = ' ', d[1] = '\0' : q == h ? d[2] -= (7 - r) : 0;
            cout_n(d, BarWidth);
            cout_n(' ', Padding);
        }
        if (DrawMinMax && Height > 1)
            h == Height - 1 ? std::cout << "┬ " << *max:
                     h != 0 ? std::cout << "│"
                            : std::cout << "┴ " << *min;
        cout_n('\n', 1);
    }
}
 
int main() {
    std::random_device rd{};
    std::mt19937 gen{rd()};
 
    auto cauchy = [&gen](const float x₀, const float 𝛾) {
        std::cauchy_distribution<float> d{ x₀ /* a */, 𝛾 /* b */};
 
        const int norm = 1'00'00;
        const float cutoff = 0.005f;
 
        std::map<int, int> hist{};
        for (int n=0; n!=norm; ++n) { ++hist[std::round(d(gen))]; }
 
        std::vector<float> bars;
        std::vector<int> indices;
        for (const auto [n, p] : hist) {
            if (float x = p * (1.0/norm); cutoff < x) {
                bars.push_back(x);
                indices.push_back(n);
            }
        }
 
        std::cout << "x₀ = " << x₀ << ", 𝛾 = " << 𝛾 << ":\n";
        draw_vbars<4,3>(bars);
        for (int n : indices) { std::cout << "" << std::setw(2) << n << "  "; }
        std::cout << "\n\n";
    };
 
    cauchy(/* x₀ = */ -2.0f, /* 𝛾 = */ 0.50f);
    cauchy(/* x₀ = */ +0.0f, /* 𝛾 = */ 1.25f);
}

Possible output: 

x₀ = -2, 𝛾 = 0.5:
                    ███                     ┬ 0.5006
                    ███                     │
                ▂▂▂ ███ ▁▁▁                 │
▁▁▁ ▁▁▁ ▁▁▁ ▃▃▃ ███ ███ ███ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.0076
-7  -6  -5  -4  -3  -2  -1   0   1   2   3  
 
x₀ = 0, 𝛾 = 1.25:
                                ███                                 ┬ 0.2539
                            ▅▅▅ ███ ▃▃▃                             │
                        ▁▁▁ ███ ███ ███ ▁▁▁                         │
▁▁▁ ▁▁▁ ▁▁▁ ▁▁▁ ▃▃▃ ▅▅▅ ███ ███ ███ ███ ███ ▅▅▅ ▃▃▃ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.0058
-8  -7  -6  -5  -4  -3  -2  -1   0   1   2   3   4   5   6   7   9

External links

Weisstein, Eric W. "Cauchy Distribution." From MathWorld--A Wolfram Web Resource.

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